Best use case
51mee-resume-parse is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
简历解析。触发场景：用户上传简历文件要求解析、提取结构化信息。
Teams using 51mee-resume-parse should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/51mee-resume-parse/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How 51mee-resume-parse Compares
| Feature / Agent | 51mee-resume-parse | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
简历解析。触发场景：用户上传简历文件要求解析、提取结构化信息。
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# 简历解析技能
## 功能说明
读取简历文件（PDF/DOC/DOCX/JPG/PNG），使用大模型提取结构化信息。
## 处理流程
1. **读取文件** - 用户上传简历时，读取文件内容
2. **提取文本** - 从文件中提取纯文本内容
3. **调用大模型** - 使用以下 prompt 解析
4. **返回 JSON** - 解析结果为结构化数据
## Prompt 模板
```
```html
{简历文本内容}
```
扮演一个简历分析专家，详细地分析上面的简历
1. 按照下方的typescript结构定义，返回json格式的ResumeInfo结构
2. 有数据就填上数据，简历上没有提到，相应的值即为null，绝对不要虚构新的或者删除定义中的字段
3. 不要做任何解释，直接返回json
4. 日期格式："Y-m-d"，如 "2025-01-01"; 年格式："Y"，如 "2025"
5. 手机号无区号，如"19821450628"
```typescript
export interface WorkExperience {
startDate: string | null;
endDate: string | null;
company: string;
industry: string | null;
department: string | null;
positionName: string;
blueCollarPosition: boolean | null;
responsibility: string | null;
workPerformance: string | null;
current: boolean | null;
workDesc: string | null;
};
export interface ProjectExperience {
name: string;
startDate: string | null;
endDate: string | null;
roleName: string | null;
projectDesc: string | null;
};
export interface EducationExperience {
startDate: string | null;
endDate: string | null;
school: string;
major: string | null;
degreeName: string | null; // 高中、本科、专科、硕士、博士、其它
};
export interface ResumeInfo {
name: string | null;
gender: number | null; // 0=男, 1=女
age: string | null;
birthday: string | null;
description: string | null;
workExpList: WorkExperience[];
projExpList: ProjectExperience[];
eduExpList: EducationExperience[];
expectPosition: {
positionName: string | null;
lowSalary: number | null;
highSalary: number | null;
locationName: string | null;
};
contact: {
phone: string | null;
weixin: string | null;
email: string | null;
};
keywords: string[];
awards: string[];
englishCertificates: string[];
professionalSkills: string;
}
```
```
## 返回数据结构
```json
{
"name": "张三",
"gender": 0,
"age": "30",
"birthday": "1995-01-15",
"description": "5年Java开发经验...",
"workExpList": [...],
"projExpList": [...],
"eduExpList": [...],
"expectPosition": {...},
"contact": {...},
"keywords": ["Java", "Spring"],
"awards": ["优秀员工"],
"englishCertificates": ["CET-6"],
"professionalSkills": "精通Java..."
}
```
## 输出格式
```markdown
## 简历解析结果
### 基本信息
- **姓名**: [name]
- **性别**: [男/女]
- **年龄**: [age]
- **生日**: [birthday]
### 联系方式
- **手机**: [phone]
- **微信**: [weixin]
- **邮箱**: [email]
### 工作经历
[遍历 workExpList]
### 项目经历
[遍历 projExpList]
### 教育经历
[遍历 eduExpList]
### 期望职位
- **职位**: [positionName]
- **薪资**: [lowSalary]K-[highSalary]K
- **地点**: [locationName]
### 关键词
[keywords]
### 奖项
[awards]
### 英语证书
[englishCertificates]
### 专业技能
[professionalSkills]
```
## 注意事项
- 支持格式：PDF、DOC、DOCX、JPG、PNG
- 日期格式统一为 `Y-m-d`
- 没有 的字段填 `null`
- 直接返回 JSON，不要额外解释Related Skills
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